粮食产量预测理论、方法与应用Ⅳ.粮食估产理论、模型及其应用

粮食估产的“通道-概率”理论：把属于最近通道的历年来的产量划分为5个气候年型通道,即丰产年、偏丰年、平产年、偏欠年、欠产年;计算产量出现在5个气候年型中的频率作为概率使用,估产年的初始估产值等于预测年各通道内平均产量与概率之积的和;估产值等于初始估产值与气候年型修正参数之积,专家根据当年气候条件和作物长势实时确定修正参数。预报单元为全国、省和县。应用结果表明：国家尺度上不需要修正,省和县级尺度需要气候年型参数修正;预测误差在3％以内;所述估产理论严谨、方法简单,参数少,参数来自原始数据本身和专家经验,易于推广使用。     

粮食产量预测理论、方法与应用Ⅴ.粮食潜力实现率及其评价方法

为说明粮食潜力与估产的关系,定义了“粮食潜力实现率”的概念,它是与粮食潜力预测值相比,当年实际达到或能够达到的百分比,它将潜力值和当年估产值或实际产量结合在一起,可用来评价潜力实际达到的程度,并可反映气候年型。应用结果表明：2010年各省单产和总产潜力平均实现率围绕100％波动,说明科技进步对增产仍然起到支撑作用,而1999-2008年各省单产和总产潜力平均实现率低于100％,说明科技进步对增产作用在减小。因此,粮食潜力实现率可以用来评价粮食增产趋势和科技进步的贡献,其方法实用、误差小。     

利用数码相片对冬小麦生物量的试算

数码相片属于地面遥感资料的一种,被广泛应用于实地调查中.然而,目前利用数码相片对植被生物量进行推算的研究很少.利用数码相片提取小麦生长期的小麦覆盖度,结合地面实测叶面积指数(LAI)、归一化植被指数(NDVI)和小麦生物量,分析小麦覆盖度与LAI,NDVI,生物量与小麦覆盖度、LAI,NDVI各自的相关系数,建立各自合适的回归模型推算冬小麦的生物量.结果表明,在小麦生长期,小麦覆盖度与LAI,NDVI的相关系数R2分别达到0.765,0.896,生物量与小麦覆盖度、LAI,NDVI的相关系数R2分别为0.774,0.876,0.712,生物量与其小麦覆盖度、LAI,NDVI之间具有很高的相关性,多元回归分析效果更好,系数R2达0.891.结果说明,在不破坏植被生长状态的情况下,基于数码相片可有效地推算小麦的生物量,这为大面积实地测量和遥感监测作物长势及其生物量估算提供了理论参考依据.     

山区县域植被覆盖度遥感估算研究——以沂源县为例

为分析典型山区县域城市——沂源县植被覆盖的时空变化情况,通过获取Landsat8_OLI数据计算NDVI指数,进一步利用像元二分模型实现对地表植被覆盖度的估算。结果表明:(1) NDVI能够有效准确地获取地表植物群落的生长发展状况;(2)将求取的植被覆盖度和地表实际数据通过统计描述特征进行相互验证,总体精度约为80%,验证了像元二分模型的可行性;(3)沂源县植被覆盖度呈现东高西低的总体趋势,植被覆盖度与人类活动成整体负相关关系。     

粮食产量预测理论、方法与应用Ⅲ.粮食生产潜力中、长期预测理论、模型及其应用

粮食生产潜力中、长期预测的目的是为国家中、长期粮食生产规划提供科学依据。粮食生产潜力中、长期预测的“双向预测理论”：从若干个预测模型中选择出2个模型,一个模型预测的未来产量是持续增加的,体现产量持续增加的科技进步力量;另一个模型预测的未来产量是先增加后减少或持续减少的,体现影响产量持续增加的负面综合因素力量。应用结果表明：模型可预测未来1~10年的粮食生产潜力,平均预测误差在5％以内。大量案例证明粮食生产潜力中、长期预测的“双向预测理论”是科学的、方法是通用的、结果是实用的。     

1998~2008年川西北若尔盖高原NDVI变化趋势分析

本文利用Mann-Kendall非参数检验方法对川西北若尔盖高原1998~2008年10年逐旬共372景的SPOT-VEGITATION归一化植被指数(NDVI)进行变化趋势检验。结果表明:川西北若尔盖高原1998~2008十年来的NDVI变化趋势以衰减为主导,其中衰减区域的面积比例为47.8%,而增长区域的面积比例仅为22.0%。若尔盖高原植被衰减区主要分布在海拔3500~4000米的高程带上,气候变化和人类活动是导致NDVI变化的主要因素。     

平度市粮食生产效率与乡村旅游发展研究

选择国家优质商品粮生产基地——山东省平度市为研究样本,利用综合评价法,在粮农成本数据的基础上构建了粮食生产效率评价指标体系并分析了平度市粮食生产效率动态变化趋势。在此基础上,利用相关分析法测度和分析了乡村旅游发展与粮食生产效率的相关性。结果表明:乡村旅游发展对粮食生产效率呈现出高度正相关性;在商品粮产区通过大力发展乡村旅游来增加农民收入,不但会使粮农提高生产投入和粮食单产水平,而且会大大改善粮食生产的土地环境,使稀缺的粮食生产资源得到可持续利用,达到保障国家粮食安全的目的。     

基于人工神经网络模型预测2017~2018年成都市危险废物增量研究

危险废物对环境或者人体健康会造成有害影响,有效地预测其产量是优化管理和合理处置的重要依据。以2008~2016年成都市危险废物产生量为基础,通过数据带入和整合及综合各参数因子的影响,利用人工神经网络模型预测方法客观反映并预测成都市危废产量的变化趋势。结果表明该模型预测2017~2018年成都市危险废物年产量分别达到24.46万t和26.88万t,模拟精度偏差低。因此,人工神经网络模型可以作为一种预测危险废物产生量的工具,其预测结果可以为职能部门提供决策参考。     

基于GIS-CA-Markov的白马河流域土地利用变化模拟分析

土地利用/覆被变化的预测模拟研究对探索土地利用变化的规律与方向,实现可持续发展具有十分重要的意义。以济宁市白马河流域为例,以不同时期的Landsat TM遥感影像为数据源,首先利用CA-Markov模型对2010年和2015年白马河流域的土地利用进行预测并检验其模拟精度,在较适宜的尺度条件下预测研究区2020年的土地利用分类。结果表明:对2015年白马河流域实际土地利用图与预测图进行Kappa系数一致性检验,模拟精度较高为0.9121,表明预测与实际几乎完全一致。2005—2020年,白马河流域建设用地和水域增加,建设用地增加最明显,增加了89.04%;耕地、林地、草地和未利用地减少,草地减少最明显,减少了31.06%。2020年白马河流域土地利用变化的预测研究结果可以为该区土地利用/覆被动态监测和可持续发展提供依据。     

基于灰色B P神经网络碳排放交易价格预测

在对中国碳排放交易市场碳交易价格形成机制讨论的基础上,提出了预测指标体系。利用2017年1月1日—2018年9月30日广州碳交易市场碳交易价格数据和指标体系中各预测变量的数据,应用Lasso回归方法对变量进行筛选,建立灰色BP神经网络对碳交易价格进行预测。预测模型对于10期以内短期预测平均相对绝对误差(MAPE)小于4%,预测精度较高。     

The Potential Influence of Seasonal Climate Variables on the Net Primary Production of Forests in Eastern China

Knowledge of the effects of climate factors on net primary production (NPP) is pivotal to understanding ecosystem processes in the terrestrial carbon cycle. Our goal was to evaluate four different categories of effects (physical, climatic, NDVI, and all effects[global]) as predictors of forest NPP in eastern China. We developed regression models with data from 221 NPP in eastern China and identified the best model with each of the four categories of effects. Models explained a large part of the variability in NPP, ranging from 46.8% in global model to 36.5% in NDVI model. In the most supported global model, winter temperature and sunshine duration negatively affected NPP, while winter precipitation positively affected NPP. Thus, winter climate conditions play an important role in modulating forest NPP of eastern China. Spring temperature had a positive affect on NPP, which was likely because a favorable warm climate in the early growing season promotes forest growth. Forest NPP was also negatively affected by summer and autumn temperatures, possibly because these are related to temperature induced drought stress. In the NDVI model, forest NPP was affected by NDVI in spring (positive), summer (negative) and winter (negative) seasons. Our study provides insight into seasonal effects of climate and NPP of forest in China, as well as useful knowledge for the development of climate-vegetation models.     

陕西关中地区旅游流"井喷效应"的时空演变规律

旅游流"井喷现象"是特殊时段旅游流时空分布的特殊现象之一,其时空分布规律研究有助于旅游目的地的科学管理参照.选取关中地区旅游资源丰富的西安、宝鸡、华山三地作为案例,建立"黄金周"客流周内波动指数R,周内分布偏度指数G,并使用相关分析和Pearson相关系数,分析陕西关中地区特殊时段内旅游流"井喷效应"的时空演变规律.结果显示,在假日制度时间约束下,旅游流呈现"井喷现象"显著,一级旅游目的地城市的旅游资源属性、周边地区旅游资源配置和区位交通状况共同影响着游客的空间选择行为,从而影响区域旅游流的时间和空间分布.     

Land Surface Phenology and Land Surface Temperature Changes Along an Urban–Rural Gradient in Yangtze River Delta, China

Using SPOT/VGT NDVI time series images (2002–2009) and MODIS/LST images (2002–2009) smoothed by a Savitzky–Golay filter, the land surface phenology (LSP) and land surface temperature (LST), respectively, are extracted for six cities in the Yangtze River Delta, China, including Shanghai, Hangzhou, Nanjing, Changzhou, Wuxi, and Suzhou. The trends of the averaged LSP and LST are analyzed, and the relationship between these values is revealed along the urban–rural gradient. The results show that urbanization advances the start of the growing season, postpones the end of the growing season, prolongs the growing season length (GSL), and reduces the difference between maximal NDVI and minimal NDVI in a year (NDVI_amp). More obvious changes occur in surface vegetation phenology as the urbanized area is approached. The LST drops monotonously and logarithmically along the urban–rural gradient. Urbanization generally affects the LSP of the surrounding vegetation within 6 km to the urban edge. Except for GSL, the difference in the LSP between urban and rural areas has a significant logarithmic relationship with the distance to the urban edge. In addition, there is a very strong linear relationship between the LSP and the LST along the urban–rural gradient, especially within 6 km to the urban edge. The correlations between LSP and gross domestic product and population density reveal that human activities have considerable influence on the land surface vegetation growth.     

NETWORK DESIGN FOR WATER SUPPLY FORECASTING IN THE WEST1

ABSTRACT: The objective is to develop techniques to evaluate how changes in basic data networks can improve accuracy of water supply forecasts for mountainous areas. The approach used was to first quantify how additional data would improve our knowledge of winter precipitation, and second to estimate how this knowledge translates, quantitatively, into improvement in forecast accuracy. A software system called DATANET was developed to analyze each specific gage network alternative. This system sets up a fine mesh of grid points over the basin. The long-term winter mean precipitation at each grid point is estimated using a simple atmospheric model of the orographic precipitation process. The mean runoff at each grid point is computed from the long-term mean precipitation estimate. The basic runoff model is calibrated to produce the observed long-term runoff. The error analysis is accomplished by comparing the error in forecasts based on the best possible estimate of precipitation using all available data with the error in the forecasts based on the best possible estimate of winter precipitation using only the gaged data. Different data network configurations of gage sites can be compared in terms of forecast errors.     

Hydrologic Effects of NDVI Time Series in a Context of Climatic Variability in an Upstream Catchment of the Minjiang River1

Abstract: Increasing regional vegetation activity has been frequently found especially in middle and high latitude and alpine areas, but the effects of which on regional hydrology is still highly uncertain. The Upstream Catchment of Minjiang River is a large mountainous catchment covering 22,919 km² with a diverse vegetation distribution pattern, including alpine group (A), subalpine group (SA), and temperate and subtropical group (T/ST). The Seasonal Mann‐Kendall test, a nonparametric trend test method, detected consistent upward trends in all groups in monthly accumulated growing degree days (AGDD_M) time series from 1982 to 2003, but no significant trend in mean monthly precipitation (MMP) time series in any group. The alpine group had a significant (p = 0.024) upward trend in monthly Normalized Difference of Vegetation Index (NDVI) time series from 1982 to 2003, in contrast, the SA and T/ST groups had decreasing (although not significant) trends. AGDD_M plays more important role than MMP in affecting NDVI change in alpine areas, indicating temperature was the main climatic driver. In contrast, water was the main driver for the T/ST group, as indicated by the significant correlation between NDVI and MMP and a weak correlation with AGDD_M. Correlation coefficients of NDVI and river flow varied with seasons, mostly negative, especially during the growing season (April to October). A significant (p = 0.025) correlation was found only in August, indicating that an increase in peak‐NDVI decreased high flow significantly. TI‐NDVI_c, which was developed in an attempt to track the vegetation change at the catchment scale, accounted for more than 40% of the evapotranspiration increase (r² = 0.43).     

DEFINING WATERSHED-SCALE EVAPORATION USING A NORMALIZED DIFFERENCE VEGETATION INDEX1

Monthly composites of the Normalized Difference Vegetation Indices (NDVI), derived from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVILRR), were transformed linearly into monthly evaporation rates and compared with detailed hydrologic-model simulation results for five watersheds across the United States. Model-simulated monthly evaporation values showed high correlations (mean R²= .77) with NDVI-derived evaporation estimates. These latter estimates, used in a classical water balance model, resulted in equally accurate simulations of monthly runoff than when the model was run to estimate monthly evaporation via soil moisture accounting. Comparison of NDVI-derived evaporation estimates with pan data showed promise for transforming NDVI values into evaporation estimates under both wet and water-limiting conditions without resorting to the application of any kind of calibrated hydrologic models.     

Wind power potential assessment for three buoys data collection stations in the Ionian Sea using Weibull distribution function

The present article utilizes wind measurements from three buoys data collection stations in Ionian Sea to study the wind speed and power characteristics using the Weibull shape and scale parameters. Specifically, the site dependent, annual, and monthly mean patterns of mean wind speed, Weibull parameters, frequency distribution, most probable wind speed, maximum energy carrying wind speed, wind power density and wind energy density characteristics have been analyzed. The Weibull distribution was found to represent the wind speed distribution with more than 90% accuracy, in most of the cases. Moreover, the correlation between the percentages of times the wind speed was above cut-in-speed and the measured mean wind speed for the three selected sites, as the correlation between the aforementioned percentages and the scale parameter c were examined and were found linear. At all these sites, no definite increasing or decreasing trends in annual mean wind speed values could be detective over the data reporting period. The mean values of wind speed, scale parameter, most probable wind speed, maximum energy carrying wind speed, wind power and wind energy density values showed higher values during winter time and lower in summer time in Pylos and Zakynthos. Moreover, Pylos and Zakynthos were found to be the best sites from wind power harnessing point of view.     

高温干旱天气下长株潭地区PM_(2.5)的变化规律研究

以湖南省长株潭地区24个环境空气质量监测国控点数据为基础,对2013年6月~8月持续高温干旱天气条件下,长株潭地区城市PM2.5浓度的日、月变化规律,以及点位差异性分布等进行分析。结果表明,进入夏季持续高温干旱天气后,PM2.5质量浓度较冬季显著下降。受人为活动影响,位于商业区的监测站点的PM2.5较其他站点高;不同城市PM2.5的日变化规律基本一致,呈双峰型;夏季PM2.5上午出现最高值的时间比冬季提前1 h左右,商业区站点的PM2.5最高值出现的时间较其他类型站点早1~2 h。非工作日PM2.5的峰值出现在夜间和凌晨,而工作日则出现在上午9~11点。     

Yield and Water Productivity of Winter Wheat under Various Irrigation Capacities

The Agricultural Production Systems sIMulator model validated in a prior study for winter wheat was used to simulate yield, aboveground crop biomass (BM), transpiration (T), and evapotranspiration under four irrigation capacities (ICs) (0, 1.7, 2.5, and 5 mm/day) with two nitrogen (N) application rates (N1, 94 kg N/ha; N2, 160 kg N/ha) to (1) understand the performance of winter wheat under different ICs and (2) develop crop water production function under various ICs and N rates. Evaluation was based on yield, aboveground crop BM, transpiration productivity (TP), crop water productivity (WP), and irrigation WP (IWP). Simulation results showed winter wheat yield increased with increase in N application rate and IC. However, the rate of yield increase gradually reduced with additional irrigation beyond 2.5 mm/day. A 5 mm/day IC required a total of 190 mm irrigation and produced a 5%–16% yield advantage over 2.5 mm/day. This indicates it is possible to reduce groundwater use for wheat by 50% incurring only 5%–16% yield loss relative to 5 mm/day. The TP and IWP for grain were slightly higher under IC of 1.7 mm/day (15.2–16.1 kg/ha/mm and 0.98–1.6 kg/m³) when compared to 5 mm/day (14.7–15.5 kg/ha/mm and 0.6–1.06 kg/m³), respectively. Since TP and IWPs are relatively higher under lower ICs, winter wheat could be a suitable crop under lower ICs in the region. Relationship between yield–T and yield–ET was linear with a slope of 15–16 and 9.5–10 kg/ha/mm, respectively. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.